Spatial and temporal changes of land uses and its relationship with surface temperature in western Iran
A split-window algorithm has been used in the Ilam dam watershed to determine the relationship between land surface temperature (LST) and types of land use. Landsat satellite images of the TM sensor for 1990, 1995, 2000, 2005 and 2010 and Landsat 8 (OLI Sensor) for 2015 and 2018 are used. After geom...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | México |
| Institución: | UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO |
| Repositorio: | Atmósfera |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/52985 |
| Acceso en línea: | https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52985 |
| Access Level: | acceso abierto |
| Palabra clave: | Landsat satellite Split-Window algorithm Fuzzy ARTMAP Kappa coefficient Ilam dam watershed |
| Sumario: | A split-window algorithm has been used in the Ilam dam watershed to determine the relationship between land surface temperature (LST) and types of land use. Landsat satellite images of the TM sensor for 1990, 1995, 2000, 2005 and 2010 and Landsat 8 (OLI Sensor) for 2015 and 2018 are used. After geometric and radiometric corrections of satellite images, land use maps are extracted by using the fuzzy ARTMAP method. An accuracy assessment showed that the highest value of the kappa coefficient was 94% with a total accuracy of 0.95 for 2015, and the lowest kappa coefficient value was 87% with a total accuracy of 0.9 for 1990. The high values of these coefficients indicate the acceptable accuracy of using Landsat’s remote sensing data for land use detection. The most important land use change is related to dense forest and sparse forest land uses, with decreases of 20.07 and 17.04%, respectively. The minimum LST measures in 1990, 2010, and 2018 in dense forest are 21.27, 30.55 and 33.82 ºC, respectively. The maximum LSTs for the sparse forest land use in 1990 and 2010 are 52.48 and 56.09, and 56.10 ºC for the dense forest land use in 2018. As a result, the average LST in agricultural lands was lower than in sparse forest and rangeland;, which is mainly due to the high moisture content and the greater evapotranspiration rate. Land use/land cover variations from 1990 to 2018 show that all land uses have experienced an increase in LST. |
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